The method to predict roll deformation precisely and efficiently is vital for the strip shape control of a six-high rolling mill. Traditional calculation methods of roll deformation, such as the finite element method ...The method to predict roll deformation precisely and efficiently is vital for the strip shape control of a six-high rolling mill. Traditional calculation methods of roll deformation, such as the finite element method and the influence function method, have been widely used due to their accuracies. However, the required calculation time is too long to be applied to the realtime control. Therefore, a rapid calculation method for predicting roll deformation of a six-high rolling mill was proposed, which employed the finite difference method to calculate the roll deflection and used a polynomial to describe the nonlinear relationship between roll flattening and roll contact pressure. Furthermore, a new correction strategy was proposed in the iteration, where the roll center flattening and the roll flattening deviation were put forward and corrected simultaneously in the iteration process according to the static equilibrium of roll. Finally, by the comparison with traditional methods, the proposed method was proved to be more efficient and it was suitable for the online calculation of the strip shape control.展开更多
荷电状态(state of charge,SOC)和峰值功率(state of peak power,SOP)的精确估计对保障电池安全稳定运行具有重要意义。为解决传统估计算法误差高、鲁棒性差等问题,本文提出了一种基于自适应无迹卡尔曼滤波(adaptive unscented Kalman f...荷电状态(state of charge,SOC)和峰值功率(state of peak power,SOP)的精确估计对保障电池安全稳定运行具有重要意义。为解决传统估计算法误差高、鲁棒性差等问题,本文提出了一种基于自适应无迹卡尔曼滤波(adaptive unscented Kalman filtering,AUKF)和经济模型预测控制(economic model predictive control,EMPC)的全钒液流电池(all-vanadium redox batteries,VRB)SOC/SOP联合估计方法。首先,为了提高传统模型的建模精度,本文综合考虑了VRB的电化学场和流体力学场的耦合特性,建立了一个能够全面刻画VRB运行过程的综合等效电路模型,并采用人工蜂群算法(artificial bee colony algorithm,ABC)对模型参数进行离线辨识。随后,考虑到传统的UKF算法无法适应系统噪声,收敛性差,且忽略电池参数变化等缺点,本文提出了基于AUKF的在线参数辨识和SOC估计算法,通过自适应调整UKF算法的参数来提高模型的精度。结合SOC的估计结果,采用EMPC算法估计VRB的SOP,并综合考虑了电压、电流、SOC和电解液流速等约束条件。最后,设计了多种实验工况验证了本文提出的SOC/SOP联合估计算法的精度。文章研究内容能够为液流电池不同运行状态下峰值功率预测和储能电站的精准调度提供依据。展开更多
基金This work was financially supported by the National Natural Science Foundation of China （51674028）, and Fundamental Research Funds for the Central Universities （FRF-IC- 16-001）.
文摘The method to predict roll deformation precisely and efficiently is vital for the strip shape control of a six-high rolling mill. Traditional calculation methods of roll deformation, such as the finite element method and the influence function method, have been widely used due to their accuracies. However, the required calculation time is too long to be applied to the realtime control. Therefore, a rapid calculation method for predicting roll deformation of a six-high rolling mill was proposed, which employed the finite difference method to calculate the roll deflection and used a polynomial to describe the nonlinear relationship between roll flattening and roll contact pressure. Furthermore, a new correction strategy was proposed in the iteration, where the roll center flattening and the roll flattening deviation were put forward and corrected simultaneously in the iteration process according to the static equilibrium of roll. Finally, by the comparison with traditional methods, the proposed method was proved to be more efficient and it was suitable for the online calculation of the strip shape control.
